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Risk assessment in complex interacting infrastructure systems (2005)
| Content Provider | CiteSeerX |
|---|---|
| Author | Carreras, B. A. Lynch, V. E. Nkei, Bertrand Newman, D. E. Gradney, Paul Dobson, I. |
| Description | HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES |
| Abstract | Critical infrastructures have some of the characteristic properties of complex systems. They exhibit infrequent large failures events. These events, though infrequent, often obey a power law distribution in their probability versus size. This power law behavior suggests that ordinary risk analysis might not apply to these systems. It is thought that some of this behavior comes from different parts of the systems interacting with each other both in space and time. While these complex infrastructure systems can exhibit these characteristics on their own, in reality these individual infrastructure systems interact with each other in even more complex ways. This interaction can lead to increased or decreased risk of failure in the individual systems. To investigate this and to formulate appropriate risk assessment tools for such systems, a set of models are used to study to impact of coupling complex systems. A probabilistic model and a dynamical model that have been used to study blackout dynamics in the power transmission grid are used as paradigms. In this paper, we investigate changes in the risk models based on the power law event probability distributions, when complex systems are coupled |
| File Format | |
| Publisher Date | 2005-01-01 |
| Access Restriction | Open |
| Subject Keyword | Complex Way Appropriate Risk Assessment Tool Infrequent Large Failure Event Complex System Risk Assessment Individual Infrastructure System Ordinary Risk Analysis Power Law Behavior Complex Infrastructure System Critical Infrastructure Power Transmission Grid Power Law Event Probability Distribution Different Part Characteristic Property Dynamical Model Risk Model Power Law Distribution Complex Interacting Infrastructure System Individual System Probabilistic Model |
| Content Type | Text |
| Resource Type | Conference Proceedings Article |
